Abstract: The present investigation was carried out to study area, production and productivity trends and growth rates of tobacco (Nicotiana tabacum) crop grown in Anand region of Gujarat state, India for the period 1949-50 to 2007-08 based on parametric and nonparametric regression models. In parametric models different linear, non-linear and time-series models were employed. The statistically most suited parametric models were selected on the basis of adjusted R2, significant regression co-efficients and co-efficient of determination (R2). Appropriate time-series models were fitted after judging the data for stationarity. The statistically appropriate model was selected on the basis of various goodness of fit criteria viz., Akaike’s information criterion, Bayesian information criterion, Root mean square error, Mean absolute error, assumptions of normality and independence of residuals. In nonparametric regression optimum bandwidth was computed by cross-validation method. Epanechnikov-kernel was used as the weight function. Nonparametric estimates of underlying growth function were computed at each and every time point. Residual analysis was carried out to test the randomness. Relative growth rates of area, production and productivity were estimated based on the best fitted trend function. None of the parametric model was found suitable to fit the trends in area, production and productivity of the tobacco crop. The Nonparametric regression was finally selected as the best fitted trend function for the area, production and productivity of tobacco crop based on lower values of root mean square and mean absolute errors. Tobacco production had increased at a rate of 1.40% which was due to combined effect of increase in area and productivity at a rate of 0.02 and 1.39% per annum, respectively.